Product innovation teams don’t come to work to search databases. They come to work to identify opportunities, understand competitors and make better innovation decisions. As brands face increasing pressure to innovate faster while reducing risk, Mintel today announced GNPD Deep Research, a new capability within Mintel Global New Products Database (GNPD) that enables users to ask complex business questions in natural language and receive clear, evidence-based recommendations based on millions of product launches tracked and analysed by Mintel experts.
This marks another step in Mintel’s strategy to help consumer packaged goods (CPG) companies make smarter innovation decisions by combining the world’s richest product innovation intelligence with technology that makes it dramatically easier to use.
A new way to work with product intelligence
Innovation teams think about growth opportunities, competitive advantage and building products that succeed in market. Until now, answering those questions often required multiple database searches, extensive filtering and significant manual analysis before they could connect the dots.
Powered by advanced AI and built exclusively on Mintel’s proprietary product intelligence, GNPD Deep Research improves that experience by fundamentally changing the relationship between people and product intelligence. Instead of learning how to navigate a database, users simply ask the question they need answered.
GNPD Deep Research is only as powerful as the intelligence behind it. Unlike generic AI tools trained on publicly available information, every recommendation is grounded in GNPD’s structured product intelligence, built from millions of product launches tracked across global markets and analysed by Mintel’s experts. Every answer is transparent, verifiable and rooted in trusted data, giving clients greater confidence in the decisions they make.
“Innovation teams are being asked to make better decisions, without increasing risk,” said Matt Nelson, Global CEO, Mintel. “That’s why we’re changing the way research gets done. GNPD Deep Research fits naturally into the way our clients work, helping them get from an innovation question to a clear answer much faster. That’s the direction we believe market intelligence needs to go.”
Polly Chan, SVP, Global Product Development, Mintel, said, “Our clients have always trusted GNPD for its product intelligence. The breakthrough was making that intelligence dramatically easier to use: removing the barrier between asking a business question and receiving a clear, evidence-based recommendation. GNPD Deep Research enables more people across an organisation to answer complex innovation questions without needing deep platform expertise.”
Helping teams answer the questions that matter most
GNPD Deep Research helps innovation teams:
- Identify whitespace opportunities and emerging areas for growth
- Understand competitor activity across categories and markets
- Evaluate ingredients, claims, formats and product attributes driving innovation
- Turn hours of manual searching and analysis into trusted recommendations delivered in minutes
- Make GNPD’s product launch intelligence accessible to more teams, regardless of their level of expertise
As innovation cycles accelerate and expectations for commercial success continue to rise, GNPD Deep Research changes how quickly and easily clients can turn product intelligence into action.
Start exploring what’s next
To learn how GNPD Deep Research can help your organisation answer complex product innovation questions faster, book a personalised demo today. Mintel clients can also contact their Account Manager to learn more.
About Mintel
As a market intelligence agency, Mintel’s understanding of consumers, innovation and global markets gives clients the clarity to act and the confidence to lead. With over 50 years of expertise and millions of data points, Mintel combines the real-world understanding of its experts with cutting-edge technology to uncover patterns, predict the future and help brands make better business decisions. Next starts here.
